In this workshop we will cover:
Dr. Oscar Ospina will lead this workshop.
Point and click tools are very useful for faster and more efficient exploratory analysis than waiting on a bioinformatician that has 10 projects and will take a month to reply. However, those wanting to conduct hypothesis testing and in-depth analysis can’t circumvent coding. And so, learning to code, even little-by-little helps.
As a reminder, spatialGE can be used as point and click tool, and there are ST tools on Galaxy. Asc-Seurat may be useful but I haven’t tested it myself and it’ll require you to have Docker installed on the machine to use it.
For single-cell RNA-seq (scRNA-seq) and spatial transcriptomics (ST) analyses, start with the Seurat tutorials and aim to understand what each step is doing. (For those wanting to use/learn Python, Scanpy and Squidpy are good starting points.) - Example Seurat scRNA-seq tutorial - Example Seurat ST tutorial - Scanpy tutorials for scRNA-seq - Squidpy tutorials for ST
There is a wealth of data sets available (scRNA and ST). I suggest the Gene Expression Omnibus (GEO), CROST, or TCGA.
Also remember: what matters is to start! Don’t wait until you fell you can learn a lot. Just start with the tutorials and know that learning takes time, but it pays off. Lastly, don’t be afraid to reach out for help/guidance. Most people are willing to help. I certainly am.